Data & AI Engineering Intern: Build ML Pipelines at Scale

Cisco; Milpitas (CA); On-site; USD 42,000 - 60,000; Full time

Job summary

Cisco in Milpitas, CA is offering a data science internship focused on building scalable data pipelines and ML workflows. You will apply Python to power real-world products, train models with PyTorch or scikit-learn, and help deploy them at scale.

You’ll work with Spark and Kubernetes to orchestrate data solutions, ensuring performance and reliability as our AI-driven platforms process large datasets. This role offers hands-on learning and collaboration with experienced engineers.

Qualifications

• Currently enrolled in an undergraduate or Master’s degree program.
• Expected to continue enrollment in degree program following completion of the internship.
• Proficient in Python and core data structures, demonstrated through at least one academic, personal, or professional project.
• Exposure to at least one ML framework: TensorFlow, PyTorch, or scikit-learn.
• Working knowledge of at least one big data/distributed processing tool: Spark, Hadoop (MapReduce), or Flink.
• Hands-on experience with at least one deployment/orchestration tool: Docker or Kubernetes.

Responsibilities

• Build data pipelines and machine learning workflows using Python.
• Develop, train, and deploy models using frameworks like PyTorch or scikit-learn, and orchestrate large-scale data solutions using Spark and Kubernetes.
• By building and scaling intelligent data pipelines, ensure platforms remain performant and reliable as we process data at scale to drive insights.

Skills

Python

Data pipelines

Machine learning

Education

Undergraduate degree program (Associate's or Bachelor's) with 2 years of work experience

Master’s degree program with 0 years of work experience

Tools

Spark

Hadoop

Docker

Kubernetes

Job description

Cisco in Milpitas, CA is offering a data science internship focused on building scalable data pipelines and ML workflows. You will apply Python to power real-world products, train models with PyTorch or scikit-learn, and help deploy them at scale.

You’ll work with Spark and Kubernetes to orchestrate data solutions, ensuring performance and reliability as our AI-driven platforms process large datasets. This role offers hands-on learning and collaboration with experienced engineers.